The performance of wireless communications systems may be significantly improved by using multi-antenna techniques. Such techniques rely on the use of multiple antennas at the receiver and/or the transmitter, in combination with signal processing. Performance improvement is made possible because the antennas are spaced a certain distance apart from each other. The relation between the antenna distance and the mutual correlation between the radio-channel fading experienced by the signals at the different antennas can then be exploited in different ways depending on the antenna configuration, for instance to achieve transmit diversity, beam-forming or spatial multiplexing.
Transmit diversity is when an identical signal, or data stream, is being transmitted from multiple antennas. Because of the spatial distance between the antennas, the same signal will thus be transmitted over several independent channels with different characteristics. This improves the likelihood that the signal can be correctly decoded at the receiver end, because it is unlikely that all the channels will fade simultaneously.
In spatial multiplexing, a number of different data streams are transmitted on the same bandwidth, i.e. the same radio resources, from multiple transmit antennas. The streams may originate from a single user, in the case where the user equipment (UE) is provided with multiple antennas, or from different users, which are scheduled for transmission on the same radio resources. The data streams are separated again on the receiver side by the receive antennas. Thus, spatial multiplexing requires multiple antennas at both the transmitter and receiver sides. In closed-loop spatial multiplexing, the transmitter also receives feedback from the receiver in the form of channel information. This enables the transmitter to improve signal quality by adapting to the actual channel conditions as experienced by the receiver.
The use of multiple antennas at both transmitter and receiver is generally referred to as Multiple-Input/Multiple-Output (MIMO). MIMO transmission and reception can be used in several ways to improve the data transmission reliability and to increase the spectrum efficiency and the capacity of wireless networks. The 3GPP standard allows taking advantage of MIMO transmission by defining MIMO modes, i.e. a set of different MIMO transmission schemes. The system may switch between different MIMO modes depending on the channel conditions. For instance, the Long-Term Evolution (LTE) standard, also referred to as Evolved Universal Terrestrial Radio Access Network (E-UTRAN), defines seven such MIMO modes, including single antenna port transmission, closed loop spatial multiplexing and multi-user MIMO (MU MIMO) mode.
MU MIMO allows multiple users to spatially share time and frequency resources, such as orthogonal frequency division multiple access (OFDMA) resource blocks. Thus, MU MIMO is a natural extension of single user multi-stream transmissions by allowing the multiple spatial streams to belong to different users.
State of the art MIMO scheduling algorithms are typically concerned with the number of spatial streams multiplexed on such resources, and are directed mainly to single-user MIMO (SU MIMO). In the case of multi-user MIMO, the multiple spatial data streams may belong to different users, and therefore MU MIMO algorithms also deal with the “pairing” of users, that is, determining which users share the same time, frequency and code resources. The pairing is affected by the maximum number of data streams that can be reliably decoded by the receiver at a certain point in time. For example, the number of uplink data streams that can be decoded by a base station under a predefined bit error rate (BER) target depends on the number of receive antennas, the receiver algorithm, the applied transmit power levels, the prevailing channel conditions and several other factors. However, it is noted that in general, the maximum number of spatially multiplexed streams that can be reliably decoded by the receiver, i.e. decodable with sufficiently low bit error rate (BER) for practical purposes is equal to the number of receive antennas. For example, a base station with four antennas will in principle not be able to successfully decode more than four spatially multiplexed streams. For this reason, such a base station should not schedule more than four uplink streams for transmission on the same resource block.
Wireless communications systems are typically cellular, i.e. the geographical area within which coverage is provided is divided into multiple smaller areas, referred to as cells. Each cell is managed by a cell site or radio base station. Such multicell systems generally define some protocol support to coordinate resource management actions, e.g. scheduling, power control, MIMO mode switching (including the switching of the number of spatially multiplexed streams), etc, such that the overall system performance is satisfactory. For instance, transmissions originating from a mobile terminal or a base station in one cell may cause interference to neighboring cells, commonly referred to as intercell or other-cell interference. In some cellular systems, this problem is mitigated by frequency planning, i.e. the frequency spectrum is divided such that neighboring cells use different parts of the spectrum. However, in state of the art OFDM systems, including the 3GPP LTE and the IEEE WiMax standards compliant cellular systems, the entire frequency spectrum is reused in all cells. That is, state of the art OFDM systems are of frequency spectrum reuse 1. Therefore, the problem of intercell interference is particularly significant in these systems.
For this reason, the LTE standard defines messages between base stations that help to coordinate the intercell and intersite interference. Two examples of such messages are the high interference indicator (HII) and the overload indicator (OI), both of which can be used by proprietary intercell interference coordination (ICIC) algorithms that can operate at the OFDM resource block level. These indicators are sent over the X2 interface, which is the interface that base stations use to communicate with each other in LTE.
The HII gives information about interference that a base station intends or expects to cause by transmissions in its own cell, while the OI gives information about what interference a base station receives, i.e. experiences, from interferers. In more detail, the HII indicates, per frequency resource, if the base station sending the HII intends to allocate the frequency resource to a user causing much interference. The OI instead states if the base station sending an OI message is experiencing high, medium or low interference per frequency resource. In LTE, both the HII and the OI work on a frequency granularity of one resource block, but they could in principle work on any, predefined frequency granularity or apply over the entire bandwidth.
The HII and OI indicators can be used proactively, a base station (BS) basically indicating in advance or requesting to/from its neighbors that certain resource blocks will be used. They may also be used reactively, i.e. a BS sends a message when it senses that the interference level is too high on certain resource blocks. Typically, the HII is used as a proactive measure while the OI is reactive.
It should be noted that the standard does not specify how the HII and OI are triggered, i.e. what interference metric should be used, what measurements the base station uses and what level of interference is considered to be high, medium, or low, respectively. Thus, the exact behavior with respect to these indicators is proprietary. However, known methods all use a metric based on a combination of received signal and interference power, e.g. SINR, normalized interference power, or interference over thermal noise (IoT). Thus, the HII and OI basically indicate if a resource block is used or not used and to what interference level.
Recall from the previous sections that in MIMO OFDM systems the same OFDM resource blocks can be used by multiple streams, and multiple users, as long as the receiver algorithm can separate the interfering and useful signals. Furthermore, in a multicell environment, the same OFDM resource can be used by users belonging to different cells, thereby increasing the interference on a given OFDM resource block. State of the art ICIC algorithms and the currently existing HII and OI indicators support efficient interference management in the time-frequency domain.
However, although it is widely recognized that MU MIMO increases intercell interference, state of the art ICIC mechanisms typically operate separately of the MU MIMO mode switching and spatial multiplexing algorithms, i.e. multi-user scheduling (including MU MIMO pairing) algorithms. Alternatively, the multicell MIMO power allocation problem, assuming that a scheduling decision has been taken, is sometimes considered as an optimization task. According to these approaches the task is to maximize the multicell sum throughput subject to per UE or per transmit antenna power constraints.
There is thus a need in the art for an improved mechanism for intercell interference coordination.